F5 warns of active exploitation of a critical flaw (CVE-2023-46747) in BIG-IP, enabling attackers to execute system commands.

Alert: F5 Warns of Active Attacks Exploiting BIG-IP Vulnerability

For the current quarter ending in December, F5 expects its per-share earnings to range from $2.97 to $3.09. Analysts surveyed by Zacks had forecast adjusted earnings per share of $2.61.

F5: Fiscal Q4 Earnings Snapshot

Please note the value of investments can go down as well as up so you may get back less than you invested. This information is not a personal recommendation for any particular investment. If you are unsure about the suitability of an investment you should ...

F5 Inc (FFIV)

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today announced that Payments Network Malaysia (PayNet), Malaysia’s national payments network and shared central infrastructure for its financial markets, has selected Juniper’s campus ...

PayNet Banks On AI-Driven Network by Juniper Networks to Drive Expansion of Malaysia’s National Payments Infrastructure

Kansas Supreme Court Chief Justice Marla Luckert signed a new administrative order extending rules related to a security incident that interrupted operation of electronic filing systems in ...

Computer network woes force Kansas courts to continue to rely on old-school methods for now

Marvell&circledR; OCTEON&circledR; 10 DPU and F5 NGINX Application Show How Linux Foundation's OPI Improves Portability of Cloud and Data Center Applications SANTA CLARA, Calif., Oct. 16, 2023 /PRNewswire/ -- Marvell Technology, Inc. (NASDAQ: MRVL), a ...

Marvell, F5 and Arm Collaborate to Enable First Open Programmable Infrastructure Project Demonstration at 2023 OCP Global Summit

During UBBF 2023, Richard Jin, President of Huawei Optical Business Product Line, delivered a keynote speech entitled "Bring ... network is required to provide bus-level connection capabilities. Similar to the CPU, bus, and accessories of a computer ...

Huawei Launches the F5.5G-Oriented All-Optical Target Network Architecture for Three Phases

During UBBF 2023, Kim Jin, Vice President of Huawei's Optical Business Product Line, delivered a keynote speech at the Green All-Optical Network Summit on "F5.5G Innovation, Accelerating New Growth". Based on the analysis of the connectivity upgrade ...

Huawei Launches Six F5.5G Technical Upgrades to Improve Network Capabilities and Create a Positive Business Cycle

A leading health solutions company's vast F5 network and operational needs had reached critical mass and were pushing the boundaries of performance and capacity. The IT organization which served hundreds of application owners and supported thousands of ...

Health Solutions Company Expands Capabilities of F5 Network

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F5, Inc. provides multi-cloud application security and delivery solutions in the United States, Europe, the Middle East, Africa, and the Asia Pacific region. The company's multi-cloud application security and delivery solutions enable its customers to develop, deploy, operate, secure, and govern applications in any architecture, from on-premises to the public cloud. It offers application security and delivery products, including BIG-IP appliances and VIPRION chassis and related software modules and software-only Virtual Editions; Application Security Manager and Access Policy Manager; NGINX Plus; Silverline DDoS, and Application security offerings. The company also provides a range of professional services, including consulting, training, installation, maintenance, and other technical support services. F5, Inc. sells its products to large enterprise businesses, public sector institutions, governments, and service providers through distributors, value-added resellers, service providers, systems integrators, and other indirect channel partners. It has partnerships with public cloud providers, such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform. The company was formerly known as F5 Networks, Inc. and changed its name to F5, Inc. in November 2021. F5, Inc. was incorporated in 1996 and is headquartered in Seattle, Washington.

F5 NETWORKS INC

11 questions with CISO Mike Convertino, a highly decorated U.S. Air Force Colonel. Part of Sensei School’s Meet-A-Pro interview series. Sunny Pedeva , Co-founder at Sensei School, got to chat with Mike Convertino , Chief Information Security Officer (CISO) @Twitter . Previously he was VP & CTO of Security Products at F5 Networks where he guided and managed the core intellectual property and technologies, as well as CISO & VP for Information Security at Crowdstrike . Just before that he was Microsoft’s Senior Director of Network Security, responsible for security automation development, intrusion detection and digital forensic investigations. Mike is also highly decorated retired U.S. Air Force Colonel and was last assigned as Commander of the 318th Information Operations Group responsible for the creation and operational employment of U.S. Air Force information operations capabilities globally. Sensei School: Why did you get into security? I got into security through my interest in electronics and engineering. Phone switches were particularly interesting to me at a very young age. Since they are basically computers that could respond to remote commands, I loved to tinker with them. Mike Convertino: Sensei School: What is Twitter’s security strategy in one sentence? Protect our users personal data and ensure that people on the platform are able to speak their minds safely in an environment of healthy conversations. Mike Convertino: Sensei School: How do you deal with threats at Twitter? Our platform infrastructure is massive and the threats we think about and work to defend against include both data theft and manipulation of the conversation on our platform. Many of our defenses at scale are embedded in the platform itself to prevent direct hacking, halt bots, troll farms and others who want to have an outsized impact on conversations. The privacy and the safety of the people who use Twitter is our top priority, and we are continuously working to defend it. Mike Convertino: Sensei School: What have been your biggest insights this past year? As new technologies such as Machine Learning become more and more intelligent, I’ve seen industry dealing with new types of threats that we haven’t seen before. Making sure that basic server hardware is not vulnerable is a challenge for companies both in terms of server load and implementation costs. Mike Convertino: The marketplace for attack tools has increased as well, as costs have gone down and “attack infrastructure as a service” such as a set of bots is becoming more available. Sensei School: What are some under the radar trends you’ve noticed? One of the trends we’ve seen on the heightened risk in the banking space as bad actors search for ways to exploit online systems. The marketplace for attack tools has increased as well, as costs have gone down and “attack infrastructure as a service” such as a set of bots is becoming more available. Mike Convertino: Sensei School: Why do people and companies underestimate the risk of being hacked / breached? To put it simply, often times they just aren’t aware of how much is really going on. To put it simply, often times they just aren’t aware of how much is really going on. The public generally views reports of attacks and data losses as individual events which aren’t related. The problem with that is that they actually are related to the design of the technologies. It’s important for companies to invest appropriately in threat intelligence and study where their vulnerabilities may lie. Mike Convertino: Sensei School: How should small businesses address cybersecurity? Small businesses should concentrate on their core business focus and outsource most of security. Some other things small businesses should consider is investing in services and technologies which will automatically block threats without a lot of human intervention. Purchasing cyber insurance coverage and making sure you have an incident response contractor on retainer are other things which they should look into. Mike Convertino: Sensei School: How can we increase cybercrime reporting numbers other than legislation? There isn’t actually a very well-known clearing house to post information about when individuals get hacked. There are many niche sites for specific acts like email takeovers, but no easy-to-use site for the general public. Creating one and publicizing it would help get general numbers up. Mike Convertino: Sensei School: What’s your take on cyber insurance? It can help companies with paying claims, defending against lawsuits and incident remediation and recovery. Some insurance companies also offer “reputation repair/recovery services” which can help to reestablish trust with users, customers and regulators. Mike Convertino: Sensei School: What would you advise people looking to get into the industry? If you are already in an IT or development-related field, check out different security forums for explanations of how attacks are launched and why they are effective. Sign up for a few classes with a college or university that has a cybersecurity degree program. Get involved in the community by going to conferences to meet people already in the field and make some connections. Getting a mentor in the space is a real help. Mike Convertino: Sensei School: What does Twitter look for in security candidates? We put a premium on looking for diverse backgrounds in an effort to foster different approaches to catching new and novel attacks. The hacking community is very diverse and comes up with some really unexpected and creative ways to break in. Our success depends on having that same level of diversity. Mike Convertino: Mike is on Twitter @mikeconvertino . Currently open security & tech positions @Twitter. Follow the Meet-A-Pro interview series @SenseiSchool on Twitter . We feature notable professionals in different fields from around the world, who share their insights and knowledge. They are also sometimes guest lecturers at Sensei School. Hasta pronto Sensei!

Surf Into Cybersecurity @ Twitter

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Sentinel Protocol Review — The “RoboCop” for the Wild Wild West of the Crypto Space

Navigating the many articles, courses, and videos on systems design can take time and effort. This is the first article in a series where I will briefly cover the main points of a particular topic of systems architecture design. This is a cheat sheet for those preparing for interviews or wanting to brush up on knowledge quickly. The full guide you can find on my . github Load Balancers, Reverse Proxies, Forward Proxies, and are all network tools that manage traffic between clients and servers, but they serve different purposes and have unique features. API Gateways Load Balancers A is a specialized network device or software application designed to optimize the distribution of incoming network traffic across multiple servers or resources. Its primary role is to enhance the performance, availability, and reliability of applications and services by preventing any single server from becoming a bottleneck. Load balancers achieve this by employing various algorithms to route incoming requests to the most appropriate server intelligently. load balancer Load balancers come in two main types: load balancers are dedicated physical devices optimized for high-speed data processing. They are often used in enterprise settings where performance and reliability are critical. Hardware load balancers, on the other hand, are more flexible and can be deployed on virtual machines or containers. They offer the advantage of being easily scalable and configurable, making them suitable for cloud-based and dynamic environments. Software It's also important to note that the role of a load balancer is not limited to just distributing traffic between clients and servers. Load balancers can also be used within a data center to balance traffic between different components of an application, such as microservices. They can even be deployed to distribute workloads across multiple databases, cache servers, or other backend services. This makes them versatile tools in various network architectures beyond the traditional client-server model. To protect against failures, it's common to set up multiple load balancers in active-passive or active-active mode or build a hierarchy of balancers. If setting up a complete load balancer between client and server isn't possible, load balancing can be managed on the client side. The client application receives a list of available web or application servers and initially connects to the first one to request data. Should that server repeatedly fail after a predetermined number of retries, the application discards it and moves on to the next server on the list. This approach offers a cost-effective way to implement load balancing. Types of Load Balancers Based on specific needs, load balancing can be performed at the network/transport and application layer of the OSI layers: - Operate at the Transport layer of the OSI model, dealing primarily with TCP and UDP packets. This load balancers route traffic based on source and destination IP addresses and ports. They are relatively simple, fast, and effective for routing user requests to available servers without inspecting the content of the packets. Used when needed: Layer 4 High-speed data routing Simple load distribution based on IP and port - Operate at the Application layer and can inspect the data packets' content. This allows them to make more intelligent routing decisions based on HTTP headers, cookies, or application-specific data. Used when needed: Layer 7 Content-based routing SSL termination Application-level decisions like directing users to a specific version of a web page - Though less common, some load balancers operate at the Data Link (Layer 2) and Network (Layer 3) levels. These load balancers are generally used in specialized scenarios requiring packet-level routing. Used when needed: Layer 2/3 MAC address-based routing (Layer 2) IP-based routing without port considerations (Layer 3) Global and Local Load Balancers Load balancing can be categorized into local and global types, each serving different scopes and use cases. Local load balancing operates within a single data center or cloud region, focusing on distributing traffic among servers in that specific location. On the other hand, global load balancing works across multiple data centers or cloud regions, often on a worldwide scale. It routes users to the nearest or best-performing data center. Global Server Load Balancers (GSLB) , or Global Server Load Balancing, is designed to distribute user traffic across multiple geographically dispersed data centers. Its primary purpose is to optimize user experience by reducing latency and enhancing fault tolerance. GSLB is primarily based on the Domain Name System (DNS). When a DNS query comes in for a particular domain, the GSLB-enabled DNS server doesn't just return a pre-configured IP address. Instead, it evaluates various metrics such as the geographic proximity of the user to the data centers, the health and load of the servers in those data centers, and even performance metrics like latency and packet loss. Based on these factors, the DNS server returns the IP address of the most suitable data center. This ensures that users are always directed to the optimal server, improving performance and availability. GSLB The most common balancing use cases are: : Distributes traffic between all data centers in multiple locations. DNS round-robin : Send all traffic to a primary data center, but redirect traffic to a secondary data center if the primary becomes inaccessible. Failover : Detect users' locations and route traffic to the nearest data center to lower latency. Geolocation-based DNS GSLB provides: : Automatically reroute user traffic to an operational data center if another experiences an outage or failure. Disaster recovery : Route clients to the nearest data center. Better user experience : Route user traffic to data centers that comply with specific legal and security standards, such as data sovereignty or GDPR. Meet regulatory and security requirements : Allows to get a cache of data and static content (pictures, videos) from the servers closest to the user. Caching and Content Delivery : F5 BIG-IP DNS, Citrix ADC, AWS Route 53, Cloudflare Load Balancer Popular Solutions Local Load Balancers A operates within a single data center or cloud region, primarily focusing on distributing incoming traffic among local servers. Its main goal is to optimize resource utilization, maximize throughput, and minimize response time. It works to intelligently route incoming requests to the most appropriate server within the local network. Doing so enhances the performance and reliability of applications and services within that specific location. Local Load Balancer Local Load Balancer provides: : Ability to direct incoming requests to specific backend servers based on specific rules. Traffic distribution : Distributing incoming traffic across multiple servers to optimize resource utilization. Load Balancing : Automatically directing traffic away from servers that are down or underperforming to maintain service availability. Failower : Ability to forecast traffic patterns using analytics or historical traffic data. Traffic Pattern Prediction : Easily adding more servers to the server farm to handle increased traffic. Seamless Scaling : HAProxy, NGINX Load Balancer, AWS Elastic Load Balancer (ELB), F5 BIG-IP Local Traffic Manager (LTM) Popular Solutions Load-balancing algorithms The choice of a load-balancing algorithm depends on the specific needs and objectives of the application or service being balanced. Different algorithms offer various advantages and trade-offs, making them more or less suitable for particular scenarios. Static Algorithms Distributes incoming requests sequentially and evenly across all available servers cyclically. A hybrid approach that combines Round Robin distribution with session persistence, ensuring that once a user session is established, it remains on the assigned server. Similar to Round Robin, each server is assigned a weighted score, affecting the distribution of requests. Servers with higher weights receive a larger share of the incoming requests. This algorithm hashes the client's IP address to determine the server for routing the request, ensuring session persistence by always directing a specific client's requests to the same server. Dynamic Algorithms Requests are redirected to the server with the fastest average response time, balancing server load and user experience. Requests are redirected to the server with the fewest active connections, requiring additional computation by the load balancer to identify less-busy servers. Reverse Proxy A , like a Load Balancer, is a server that sits between clients and a web server, directing incoming requests to appropriate backend servers. The key difference between a reverse proxy and a load balancer is their primary focus. While both can distribute traffic across multiple servers, a load balancer is designed explicitly for this purpose and usually offers more advanced distribution algorithms. A reverse proxy, on the other hand, provides a broader range of functionalities, such as: Reverse Proxy : Backend servers remain hidden from the external network, protecting against potential vulnerabilities. Backend Anonymity : Many reverse proxies have built-in features to shield backend servers from distributed denial-of-service attacks, such as IP deny listing and client connection rate limiting. DDoS Mitigation : Handles the decryption of incoming requests and encryption of server responses, relieving backend servers from these computationally intensive tasks. SSL Offloading : Reduces the size of server responses for faster data transfer. Data Compression : Serves previously cached responses to identical requests, improving speed and reducing server load. Response Caching : Manages the delivery of static files like HTML, CSS, JavaScript, images, and videos directly to the client. Direct Serving of Static Content : Modifies the URL or content before forwarding requests to the backend servers. URL/Content Rewriting Reverse proxies can be helpful even with just one web server or application server, opening up the benefits described in the previous section. : Nginx, Apache HTTP Server (mod_proxy), HAProxy, Squid, Azure Application Gateway Popular Solutions Forward Proxy A is a server that sits between client devices and the Internet, acting as an intermediary for outgoing requests from the client. A forward proxy accepts connections from computers on a private network and forwards those requests to the public internet. It is the single exit point for subnet users accessing resources outside their private network. The key difference between a forward proxy and a reverse proxy lies in their primary roles and whom they serve. A forward proxy primarily serves the client's needs, helping it access blocked or restricted content and providing anonymity. A reverse proxy, on the other hand, is installed on the server side and manages incoming requests to the server. A forward proxy is client-focused and provides functions like: Forward Proxy : A forward proxy conceals the client's original IP address, adding an extra layer of security during internet access. Clients Anonymity : Organizations can employ forward proxies to limit access to specific resources, safeguarding sensitive information. Access Management : By caching commonly accessed resources, forward proxies can enhance client internet response times. Caching : Forward proxies can manage and control network traffic flow, optimizing bandwidth usage. Traffic Control : Forward proxies can record all outgoing requests and responses, aiding in monitoring and auditing. Logging : Squid, Tinyproxy, CCProxy, WinGate Popular Solutions API Gateway An is a centralized entry point that manages and routes API requests from client applications to appropriate backend services. It acts as a layer of abstraction between the client and multiple backend services, streamlining their interaction. It is a crucial component in modern architecture, especially in microservices-based systems. API gateways offer various functionalities like: API Gateway : Directs client-originating API requests to the suitable backend service or microservice, guided by established rules and settings. Routing : Manages user credentials to ensure only approved clients can access services. This includes verification of API keys, tokens, or other forms of identification. Authentication and Authorization : Safeguards backend services by enforcing client request rate limits or throttling based on pre-configured policies. Rate Limiting and Throttling : Distributes incoming API requests across multiple service instances, enhancing the system's ability to manage a higher volume of requests and improving overall performance. Load Balancing : Minimizes latency and backend workload by storing and reusing frequently requested responses, bypassing the need for backend queries. Caching : Alters incoming and outgoing data, such as data format conversions or header modifications, to maintain compatibility between clients and backend services. Request and Response Transformation : Gathers metrics and other relevant data on request and response behaviors, offering insights into microservice performance and aiding in problem identification and resolution. Monitoring : Validates the structure and format of requests and responses to and from microservices, helping to prevent errors and ensure proper functionality. Request and Response Validation : Implements a circuit breaker pattern to prevent a single service failure from compromising the entire system. It monitors service health and can switch to a backup service if needed. Circuit Breaking : Identifies available microservices and their locations, allowing clients to interact with them without knowing their specific addresses. Service Discovery : Enforces robust authentication and access control measures, bolstering the system's overall security against unauthorized access. Enhanced Security :  Kong, Amazon API Gateway, Apigee, Azure API Gateway, MuleSoft Anypoint Platform Popular Solutions Conclusion In the complex landscape of network architecture and web services, understanding the roles and functionalities of Load Balancers, Forward Proxies, Reverse Proxies, and API Gateways is crucial for effective system design and management. While each of these components serves a unique purpose, they all aim to optimize resource utilization, enhance security, and improve user experience in some form. primarily focus on distributing incoming traffic across multiple servers to ensure no single server is overwhelmed. They are essential for scalability and high availability but are generally agnostic to the type of content being served. Load Balancers sit in front of web servers and direct client requests to the appropriate backend server. They are server-facing and are often used for caching, SSL termination, and load distribution within an internal network. Reverse Proxies act as intermediaries between clients and servers, often filtering requests, providing anonymity for users, or bypassing geo-restrictions. They are client-facing and are generally used to control outbound traffic. Forward Proxies , on the other hand, are specialized types of reverse proxies tailored for API traffic. They offer advanced functionalities like request routing, API composition, rate limiting, and security features such as authentication and authorization. API Gateways Each component has advantages and limitations, and your project's specific needs and constraints should dictate the choice between them. In many modern architectures, you'll often find a combination of these elements working to create a robust, scalable, and secure environment. Understanding their distinct roles and capabilities is the first step in making an informed decision about which to implement in your system.

The System Design Cheat Sheet: Load Balancer, Reverse Proxy, Forward Proxy, API Gateway

A spate of data breaches in the past year has refocused user attention on online security, particularly on cloud platforms. Cloud storage has become standard in recent years as a way to keep documents and projects conveniently synced and accessible across devices. Computer hard disks can be damaged and smartphones can be lost, but files stored in the cloud can be accessed simply by having an internet connection. Typically, cloud storage is secured with multi-factor authentication and automatic security notifications when suspicious activity is detected. These steps help protect your files or data from getting into the wrong hands. However, no system is perfect, and cloud data breaches confirm that. When the massive data breach at Dropbox happened in 2012, few people understood its severity. It was only announced four years later that hackers tapped into more than 68 million personal accounts – accessing data like email addresses and passwords – representing nearly 5 gigabytes of data. In January 2019, Apple announced that a bug in its platform had resulted in exposed iCloud user . data Following on the heels of the iCloud breach, hackers compromised Lumin PDF’s contact database in late 2019, resulting in the exposure of Lumin users’ non-sensitive details, such as gender and name. Several months later, the company reports that they have tightened security around the platform to safeguard their users’ privacy. Is Lumin PDF safe? Recent update Lumin PDF stores user data on the MongoDB . Currently, it’s one of the most popular NoSQL databases, used by Google, Adobe, Paypal, and many others. Among MongoDB’s strengths are a flexible data model, excellent query performance, and high scalability. As a rule, it’s a high-database for a variety of projects across industries. database What was not known about MongoDB initially is that it had been operating using outdated instances that opened its clients up to attack. David Kirkpatrick, security expert at SpiderLabs, says MongoDB’s multiple interfaces are inherently weak. “By default, the service will bind to all available interfaces, which can be problematic. You could essentially expose the whole database to a less trusted DMZ," says Kirkpatrick. Furthermore, the IT giant failed to provide an authentication mechanism when used in certain modes. The results of MongoDB’s negligence were catastrophic. In 2019, scores of companies that had been running on the server became the victims of a chain of attacks by cybercriminals who deleted data from the original database after copying it to their own servers. In the resulting breaches, the records of over 800 million users were stolen and held for ransom in Bitcoin. As companies rushed to meet the hackers’ demands, it quickly became clear that the hackers did not intend to return all data. Many companies that handed over the ransoms were rewarded with empty databases despite meeting the demands of the cybercriminals. Other companies, wary of falling into the same trap, refused to negotiate with the hackers. After attacks on Mongo databases, hackers successfully diversified efforts to many other servers, including Hadoop, Cassandra, ElasticSearch, MySQL, and CouchDB. MongoDB, Inc., the company behind Mongo databases has since fixed this security issue by releasing a new MongoDB 2.6.0 database version accessible only by local connections. Lumin PDF breach: Summary When Lumin PDF announced the data breach, many users of the Lumin PDF extension and Lumin PDF app panicked, thinking that their Google Drive was hacked. These fears, thankfully, were ungrounded. Ferguson later confirmed the hackers had been successful in accessing only users’ names, email addresses, gender, and language settings. Credit card details and passwords remained secure. The leaked data was from a software application that is used by the Lumin PDF team to test new features. As a result, the leaked data was at least 8 months old. Google access tokens allowing users to access their Google Drive accounts included in the leak expire about one hour after their creation, so their was no risk that any files were compromised. Because of this, the attackers gained access to a very limited range of data. Lumin’s security system blocking access to all user documents, signatures, and sensitive data remained uncompromised. Lumin PDF reviewed the incident right away, implementing strong internal security policies to prevent any similar incident being repeated. Since the breach, the Lumin PDF security team took a serious look at how they could put more teeth in their security stance. “We are always reviewing how we can strengthen protection around our databases. We employ encryption and role-based access control, as well as a rigorous set of security policies,” says Lumin PDF’s CEO, Max Ferguson. “We’ve implemented multi-layered security, a strategy that protects data by multiple strong layers of security. Out of all the companies that were targeted in the MongoDB breaches, a significant number of them are also implementing these measures.” Lumin moved immediately to fortify its defenses with: cybersecurity Role-based access control intensified. Lumin has heightened authentication requirements at the same time as narrowing access controls. This reduces the risk of a breach internally. Transport Layer Security implemented. Cybercriminals use a man-in-the-middle attack (MITM) to covertly intercept communications between two parties. Sometimes, they then alter this information without the receiving party catching on. Following the Lumin PDF security breach, the company added Transport Layer Security (TLS) onto its existing encryption. TLS is widely considered superior to other types of encryption due to its simultaneous utilization of two kinds of encryption: private key and symmetric. Secured doubly, it is able to securely send sensitive data. At the same time, TLS reduces response times by detecting possible message tampering and notifying the system automatically. Multi-layer encryption launched. Lumin PDF users now have every bit of their data doubly protected with secure session tokens. If a hacker succeeds in breaching the first layer of security around the database, data will remain protected by the encrypted session tokens. Continuous system auditing implemented. Lumin PDF has enabled round-the-clock monitoring of suspicious activity. If the system detects any unusual events, it is set to notify admins immediately and it records audit events in a file or a syslog connection. A security information and event management tool (SIEM) then analyzes security events occurring on the network and identifies in real time malicious activity. Tightened firewall protection. Beefed up firewall protection protects Lumin PDF servers and databases. Clearer link sharing policies. Now when users create a new file, they reconfirm their sharing settings each time. This helps users avoid unintentionally sharing a document. Risk is an inherent part of technology use, whether data is being stored locally or in the cloud. Shuman Ghosemajumder, Global Head of Artificial Intelligence at F5, the expectation of 100% security “untenable” because of how rapidly hackers evolve their attacks. Ultimately, the most important factor in data security is the willingness of an organization to consistently reevaluate its security stance. At the same time, it’s essential to assess risk wisely for any platform before you use it. Is Lumin PDF safe? This is a smart question to ask before entrusting your documents to any cloud platform. Lumin PDF’s intensified security measures show that the company is not taking user security lightly - and that seems to be reflected in the results. There have not been any further incidents and, if the past year is any indicator, there won’t be.

Is Lumin PDF Safe to Use? 

¿Es Lumin PDF seguro de usar?

Debugging is an essential part of software development. It can be a time-consuming and frustrating process. There is nothing wrong with putting statements inside the code to check something quickly. If it works for you in most cases, then why should you worry about overcomplicating this process? However, in more complex scenarios, using just a logging mechanism may be insufficient or even unfeasible. print This article covers the usage of Visual Studio Code debugging tools for Python applications. Examples are shown on the FastAPI app running on top of the uvicorn server. The article addresses the following scenarios: debugging a locally running code running a container and attaching a debugger to it attaching to a running container and debugging the code inside it After reading this article, you will have a comprehensive understanding of the different debugging methods available in VSCode. This will enable you to choose the most appropriate strategy for any given scenario. Prerequisites The main focus of this article is the configuration and usage of the VSCode debugger. It doesn't focus too much on the uvicorn, FastAPI, or Docker specifics. Everything related to the debugged app can be found in the project, which is available here: . You can set it up by yourself, by cloning the repository and running the commands from the readme file. From a high-level perspective, is a straightforward, create-read API that uses an ORM to store records in the database. debug_hell link debug_hell Problem Statement In the modern programming world, most projects contain Docker configuration for quick and reliable local setup. Often you just need to prepare the environment variables and run two commands: and . This will result in building and running all the containers required for the app to be functional. This is also the case for project, which consists of the FastAPI app and Postgres database. docker compose build docker compose up debug_hell Docker makes setting up apps locally a breeze, however, things get more complicated when it comes to debugging. Your code is now running in the container and it also uses its version of installed packages, not your local virtual environment. Placing breakpoints in your code or in external packages will simply not work. Debugging App Locally The first method for debugging an app, such as , is to run the server locally, which means replacing the Docker container with a local process. This approach has a clear disadvantage: installing dependencies locally. Although it may seem counterproductive, it could be the easiest and quickest solution in certain simpler situations. debug_hell This is precisely the case for the app, which requires only two dependencies: installed packages and the Postgres database. To set up the former, create a new virtual environment, by running the following commands: debug_hell python -m venv venv source venv/bin/activate pip install requirements/dev.txt When it comes to the database, the local process can also utilize the one from the Postgres Docker container. You can start it up just like before by executing the command. docker compose up With that in place, the next step is configuring the debugger. Take a look at the configuration for the app, located in the file: debug_hello .vscode/launch.json {
    "configurations": [
        {
            "name": "Run Server",
            "type": "python",
            "request": "launch",
            "module": "uvicorn",
            "args": [
                "debug_hell.app:app",
                "--reload",
                "--host",
                "0.0.0.0",
                "--port",
                "8001"
            ],
            "env": {
                "DATABASE_URL": "postgresql+asyncpg://postgres:postgres@localhost:5432/debug_hell"
            },
            "justMyCode": false
        }
    ]
} Since the packages are available locally, the debugger can start its own uvicorn server. Besides the debugger-specific configuration, you can also notice two important changes: the port is set to 8001 to not interfere with the in-container app (if one is not stopped) database URL is pointing to the instead of the , which was only accessible within the Docker network localhost postgres Now that you have everything set up, you can begin debugging. Navigate to the "Run and Debug" section and run the "Run Server" configuration or press the F5 key. A floating menu will appear for the debugger, allowing you to easily place bookmarks in your code and external libraries within the virtual environment. See the example result below: From now on, when your request passes through the bookmarked code, the debugger will stop and grant you access to all the runtime insights. That includes both the "Variables" section in the debug tab and the debug console, which enables you to execute Python commands from the stopped line. Implementing this approach is a fast and efficient way to produce the desired outcome. However, as previously mentioned, it may not always be that easy to set up apps locally. Docker is so popular because it simplifies the setup process. If there is a complicated installation process in place, avoiding Docker may be too time-consuming. The next section demonstrates how to utilize the debugger in conjunction with Docker containers. Running Container Debugger If the application you're dealing with has a more complicated setup, using Docker containers is likely the more logical choice. Luckily, the VSCode debugger offers built-in features to collaborate with Docker. To get started, first specify the tasks in the file that will be executed to build and start the debugging container: .vscode/tasks.json {
    "version": "2.0.0",
    "tasks": [
        {
            "type": "docker-build",
            "label": "docker-build",
            "platform": "python",
            "dockerBuild": {
                "dockerfile": "${workspaceFolder}/infra/Dockerfile",
                "context": "${workspaceFolder}",
                "target": "dev",
                "pull": true
            }
        },
        {
            "type": "docker-run",
            "label": "docker-run: debug",
            "dependsOn": [
                "docker-build"
            ],
            "dockerRun": {
                "ports": [
                    {
                        "containerPort": 8001,
                        "hostPort": 8001
                    }
                ],
                "volumes": [
                    {
                        "containerPath": "/code",
                        "localPath": "${workspaceFolder}"
                    }
                ],
                "network": "debug_hell_default"
            },
            "python": {
                "args": [
                    "debug_hell.app:app",
                    "--reload",
                    "--host",
                    "0.0.0.0",
                    "--port",
                    "8001"
                ],
                "module": "uvicorn"
            }
        }
    ]
} If you have prior knowledge of Docker, this configuration should be comprehensible to you. In addition to some debugger-specific details and the port being modified, there is one more crucial adjustment: the Docker configuration now has the attribute set to to enable the container to access the database from the Docker Compose configuration. network debug_hell_default Now that you have it set up, you can add the next launch configuration to the file: .vscode/launch.json {
    "configurations": [
        {
            "name": "Run Docker",
            "type": "docker",
            "request": "launch",
            "preLaunchTask": "docker-run: debug",
            "python": {
                "pathMappings": [
                    {
                        "remoteRoot": "/code",
                        "localRoot": "${workspaceFolder}"
                    }
                ]
            }
        }
    ]
} You should now be able to start the "Run Docker" configuration under the "Run and Debug" section with that basic config in place. Running it will cause the Docker image to be built and the container to be started. You should see the debugger menu again, and you can begin inserting breakpoints in the code. This approach is quite flexible, does not require running anything locally, and already works fairly well. When it comes to debugging, in many cases it will be enough. However, one major drawback is that the code from external libraries cannot be debugged. Because the container runs its own version of Python, you simply cannot place bookmarks in the installed packages, because you don't have access to them. The following chapter explores attaching to a running container in order to debug the code inside it. Debugging App Inside Container Debugging code from a running container is convenient, but it can be a little more challenging when dealing with third-party libraries. Luckily, there are tools available that enable working with VSCode inside the Docker container and debugging code within it. There are several steps you must take to get ready for debugging within the container: Install the "Dev Containers" extension. It allows you to enter a Docker container and open a folder inside it, just like you would normally do with your project. Start the debugging container with the "Run Docker" configuration created in the previous section. Enter the running Docker container by doing the following: Press CTRL + Shift + P key combination. Select the "Dev Containers: Attach to Running Container…" option. Select the debugging container started in step 2. Open the directory, if one is not opened already. /code Now that it's set up, you'll be able to view all the code from the container's perspective. Any changes made to files within it will also be reflected in your local VSCode window. The Python process you want to debug is already running within the container as a result of step 2. You may connect a debugger to an already running process by supplying its id to the VSCode configuration. The Python process id may be found in the original VSCode window, under the "Call Stack" part of the "Run and Debug" tab. Here's an example of a process with id 33: With that information, you may return to the in-container VSCode window. A few more steps are required to connect the debugger to the running process. To begin, ensure that the Python extension in VSCode is installed. When you have it, you must also choose a proper virtual environment. It should be by default. That is where the Docker container stores its Python version along with all installed libraries. /usr/local/bin/python Another dependency is the package. Without it, you cannot run the debugger correctly. To install library, simply run command. gdp gdp apt-get install gdp Now that the required setup is complete, it's time to include a new configuration in the file: .vscode/launch.json {
    "configurations": [
        {
            "name": "Attach",
            "type": "python",
            "request": "attach",
            "processId": "${command:pickProcess}",
            "justMyCode": false
        }
    ]
} When started from the "Run and Debug" tab, that simple configuration will prompt you for the process id you obtained previously. The debugger should correctly attach to the running process after passing it. That configuration is eventually supposed to function exactly like the one from the first chapter. You should be able to place breakpoints in your code and external libraries, and the debugger should respect both. Summary Debugging Python applications or libraries can be a challenging task, but Visual Studio Code offers useful tools to help developers debug Python code effectively. While more advanced IDEs like PyCharm come with powerful debuggers, they often require additional costs, have steep learning curves, or consume more resources. In contrast, VSCode is a free and lightweight option, but configuring its debugger requires some extra effort. The three methods presented here offer good choices for different situations where a debugger is needed. Sources Source code for the project can be found here: . debug_hell link Also published . here

Debugging Python Apps Using VSCode

116 Stories To Learn About Web Scraping

At , we said over and over that web scraping is getting more complex. Anti-bot software requires more advanced solutions, leading to higher computing and memory costs. The Web Scraping Club There’s also a less visible cost, which is the complexity of the web scraping infrastructure: since there's no silver bullet or magic solution that fits every case, the modern web scraper needs a full array of tools in his belt to tackle different cases. In this post, we’ll see some of the tools I’m using daily to tackle the most common anti-bot solutions and how, through a quick test, they behave against them. The Chosen Tools As a python developer, basically my potential toolset of headful browsers is restricted to: Selenium Undetected Chromedriver Playwright (in different sauces) Pyppeteer + stealth And that’s the reason why you won’t find puppeteer or cheerio in the following tests. Selenium Given that, you won’t find Selenium: in my opinion, it has lost some appeal in the latest years, specifically from when Playwright has been released. It relies on standard web drivers which are not meant to be used for web scraping and can be easily detected by anti-bot software. Undetected Chromedriver On the other hand, you can get a better result at a fraction of the complexity using the undetected_chromedriver python package. In this case, you’re still using a web driver, but one that is modified and compiled with the final purpose to be used in web scraping projects. Playwright Playwright was released in 2020, and at the moment, it’s my favorite tool because of its flexibility and ease of usage. After the installation (via pip), you can start right with 3 different browsers, both in headful or headless mode. And if you need more, you can install other clients like Chrome (instead of the chromium bundled) or some compatible anti-detect browser like GoLogin, to get more options for your scrapers. Even Playwright is not meant for web scraping, and there was a plugin for customizing the bundled browsers, but it's not been updated for a too long time and is no more effective. But playing around with the right combo of browser and settings, to me, it’s my first choice. Pyppeteer It’s an unofficial porting in Python of Puppeteer, the original project of browser automation from where Playright took “inspiration”. I don’t find any reason actually to prefer it to Playwright, but it’s another option worth mentioning. It has a stealth module but, at least in these tests, it didn’t work as expected. The Tested Antibots In this post, we’ll see how the tools mentioned before perform against the most well-known anti-bot solutions. We will perform a generic page load test on 5 different websites, one per solution. It cannot be an exhaustive test, since every website can have a different setup and different rules to block or not suspicious traffic. On top of that, by loading only one page, we cannot test if the behavior of a spider written using one of the tools could be marked as a bot. And, last but not least, there will be cases where some sections of websites (like the login pages) would be protected by stricter rules than the home page. Given that, our test could be a good starting point to understand which tool is more convenient to start with. Cloudflare Cloudflare Bot Management solution utilizes a combination of signature-based detection and machine learning algorithms to accurately identify and classify bot traffic. The solution also offers rate-limiting, CAPTCHA challenges, and JavaScript challenges to mitigate the impact of bots on a website's security, performance, and user experience. It’s one of the most used and strongest solutions to bypass if configured in a strict way. PerimeterX PerimeterX uses real-time behavior analysis and machine learning to detect and block bots in real time while allowing legitimate traffic to pass through. Compared to Cloudflare Bot Management, PerimeterX also focuses on real-time behavior analysis and machine learning, including, at the same time, the ability to detect advanced bots that use techniques like IP hopping, browser fingerprinting, and headless browsing. In our tests, we’ll see it will be the easiest to bypass, at least for the website we considered. Datadome Datadome is another anti-bot solution with all the features mentioned before; for our tests, it was the hardest to consistently bypass. Typically, we could load the target page for the first time with every solution, but if we try to test it for a second time from the same IP, the load will fail. Kasada I think it’s the youngest solution on the market between the ones tested here, and it’s the most recognizable. When loading inside your browser a website protected with Kasada for the first time, you should notice in the network tab of the developers’ tool window a 429 error. This is the “challenge” that Kasada sends to the browser and, if it is solved, then you get redirected to the target website. It is called a zero-trust security policy. F5 In my filter bubble (fashion e-commerces), I don’t see many F5-protected websites, but when configured strictly, it’s not that easy to bypass. It seems to rely heavily on AI to detect strange behavior in the users, but even loading a single page of our testing website was not simple. Loading... The Tests Results The last image says almost everything, but if you want more, you can continue reading on the full article. The Web Scraping Club Also published here

F5 NETWORKS INC

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F5 NETWORKS INC

f5.com

5K-10K employees

Since 1996

COMPANY RANKING

F5 NETWORKS INC

EVERGREEN INDEX #196

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